Job Description
Wayfair is hiring a Senior Product Manager to lead its Pricing & Marketplace Intelligence AI/ML product area — one of the highest-leverage, most technically demanding PM seats inside Wayfair's Global Supplier Technology (GST) organization. This is a rare opportunity to own a product surface where machine learning decisions directly move revenue, contribution profit, and supplier economics at massive e-commerce scale.
Wayfair's GST group builds the platforms and tools that power how suppliers do business with Wayfair and how the company manages its economics across millions of SKUs. Within that group, the Pricing & Marketplace Intelligence AI/ML team owns the systems that set and optimize prices, manage unit economics, incorporate demand and forecasting signals, and translate competitive intelligence into pricing and commercial decisions. This is a science- and ML-oriented product domain, meaning the PM in this seat will work daily alongside Applied Scientists, Data Scientists, and ML Engineers to shape the models that directly set customer-facing prices and supplier margins.
This role reports into GST leadership and carries a mandate spanning strategy, roadmap ownership, and hands-on execution across pricing and profit optimization workstreams, with a secondary focus on integrating competitor-intelligence signals into commercial decisioning.
Key Responsibilities
- Run discovery with cross-functional stakeholders — Pricing Strategy, Category Management, Supplier Management, Promotions, and Finance — to define and evolve the product vision and strategy for core pricing and profit optimization.
- Translate that vision into a sequenced, adaptive roadmap across multiple concurrent workstreams, updating it as experiments, model performance, and business priorities shift.
- Partner directly with Applied Scientists and ML Engineers to design, prioritize, and ship models and decision systems that set prices, optimize contribution profit, and fold in competitor pricing signals.
- Translate dense scientific and technical concepts into clear problem statements, requirements, and decision frameworks that non-technical business stakeholders can act on.
- Own and monitor KPIs and health metrics — revenue, contribution profit, conversion, margin, and supplier economics — to track product impact.
- Run an Agile execution cadence with Engineering and Science/ML teams, staying current on emerging techniques that could accelerate the roadmap.
- Make pricing and profit systems observable and explainable, surfacing the right levers and controls so business users can trust model-driven decisions.
- Set and track OKRs for major initiatives, keeping them aligned with stakeholder goals and Wayfair's broader financial targets.
- Drive strong cross-functional team dynamics, contributing to product craft and process improvement across GST.
- Communicate roadmap, strategy, and progress clearly — including to senior and C-level stakeholders when needed.
Requirements
- 7+ years building software, platform, data, or algorithmic products with measurable business impact, ideally in ambiguous or cross-functional environments.
- Demonstrated ownership of roadmaps for products built on data, experimentation, or algorithms — pricing, recommendations, ads, or marketplace optimization.
- Strong product instincts: comfortable moving from ambiguous discovery to requirements, tradeoffs, adoption, and measurable outcomes.
- Sharp analytical skills; able to define metrics and work hands-on in large datasets alongside data partners.
- Proven track record partnering with Data Scientists, Applied Scientists, and ML Engineers — shaping problem formulation, success metrics, and experimentation strategy.
- Hands-on comfort with SQL/GBQ, experimentation readouts, and interpreting modeling insights.
- Excellent communication and senior stakeholder management — able to simplify complex technical tradeoffs for diverse audiences.
- Bachelor's degree in a technical or quantitative field (Computer Science, Engineering, Mathematics, Economics, Statistics) or equivalent practical experience.
Preferred
- Background in pricing, revenue management, marketplace dynamics, or ad tech.
- Familiarity with A/B testing and statistical reasoning, interpreting experiment results with Science/Analytics partners.
- Prior exposure to ML-driven products — ranking, prediction, optimization, or decision systems.
- Experience in e-commerce, retail, or marketplace businesses.
- Prior work with supplier-facing or B2B platforms.
